I love this: a DSL that makes clocks out of birds and math. Really, this is a glorious little project.
The thing I bounced off isn't the high-concept art, or the abstract math. It’s the combination of the two without enough bridge between them. You have to infer too much about how the poetic layer, the mathematical notation, and the actual machinery relate.
You can do mind-expansion by induction in a math journal. This is not that venue. And this project is too good to waste by letting people walk away confused.
I’d love a very plain “one clock, end to end” walkthrough: primitives, composition, graph, rendered result.
And many more who sell crops, chemicals, power, machine parts, cars, concrete...
Many companies have billions of customers and no trace of lock-in or virality at all. You might want to shift your perspective a little and remember that there is a world outside of Silicon Valley.
Verizon competes with T-Mobile and AT&T. Comcast competes with a different arm of AT&T, Google Fiber, various older satellite internet services and now Starlink.
Outside the US, broadband providers are still huge but differences in regulation mean there are five or six of them in most markets.
Overall, I think my point still stands: claiming that you can't build a giant company without Silicon Valley's growth formula is ridiculously narrow. The vast majority of big companies are built by other methods.
No, it really isn't a good idea to base your theories of psychiatric medicine on a satirical half-hour cartoon show about swearing construction-paper children.
It is true that there are some corners of the internet where probably-healthy people meet to discuss what it's like to have disorders that they probably don't have, or in some cases disorders that might not even exist.
But you really ought to talk to some actual doctors and patients before you conclude that their problems aren't real, or can be overcome by pretending they don't exist.
South Park is poking fun at the industry, but it's humor. It doesn't tell you what the problem is. I only mentioned it because it's a good related episode :)
My point is not about pretending problems don't exist. It's about focusing on encouraging people rather than focusing on claiming who they are.
The biggest per-student spender on education in the developed world is the US:
> In 2019, the United States spent $15,500 per full-time-equivalent (FTE) student on elementary and secondary education, which was 38 percent higher than the average of Organization for Economic Cooperation and Development (OECD) member countries of $11,300 (in constant 2021 U.S. dollars). At the postsecondary level, the United States spent $37,400 per FTE student, which was more than double the average of OECD countries ($18,400; in constant 2021 U.S. dollars).
And everybody knows that US outcomes in primary and secondary education are not great. (Actually they're considerably better than many realize, but not as good as, say, Finland, which spends much less). So budgets aren't everything.
And yet, at both the top and in the broad middle, US universities have some of the best outcomes in the world. So big budgets can still be good.
Human brains are complicated. Big groups of them are more so. Transferring output of some brains to other brains in big groups is not at all straightforward.
It's no wonder people would rather swap platitudes about bigger budgets.
If you want to learn about symbolic AI, there are a lot of more recent sources than PAIP (you could try the first half of AI: A Modern Approach by Russel and Norvig), and this has been true for a while.
If you read PAIP today, the most likely reason is that you want a master class in Lisp programming and/or want to learn a lot of tricks for getting good performance out of complex programs (which used to be part of AI and is in many ways being outsourced to hardware today).
None of this is to say you shouldn't read PAIP. You absolutely should. It's awesome. But its role is different now.
Some parts of PAIP might be outdated, but it still has really current material on e.g. embedding Prolog in Lisp or building a term-rewriting system. That's relevant for pursuing current neuro-symbolic research, e.g. https://arxiv.org/pdf/2006.08381.pdf.
Other parts like coding an Eliza chatbot are indeed outdated. I have read AIMA and followed a long course that used it, but I didn't really like it. I found it too broad and shallow.
I have never given emacs a fair shot, so I can't compare the two. Neovim makes it easier to get modern editor features like treesitter and lsp support integrated into the editor. The Lua api seems to have been very well received, so the plugin ecosystem for neovim is thriving. It has also attracted a lot of people outside of the original vim niche (including me!) recently, which means there are more plugin developers who care about how things look and feel to use.
There are certainly some constrains on what plugins can achieve due to nvim being exclusively a TUI, but in my opinion the pros of the editor outweigh the cons.
As to what makes me choose neovim over vscode with a vim plugin, it's a combination of things. One thing I love is that neovim is extremely easy to configure. I also enjoy that everything follows vim rules, rather than some things like file trees or consoles having their own unique rules. I have also become dependent on some vim plugins that don't exist in vscode.
VS Code's goal is to get the low-effort 30% of devs who want something that will just work right out of the box, while providing enough functionality/customization to attract a significant fraction of the remaining 70%. And given that, it's pretty good.
But I'm skeptical it will ever be as good for someone who does want to make the investment in something like Emacs.
He's a "futurist", who's explicit job is to make hand wavey, big, shocking claims. Historically, futurists have a less than random chance at being right about the future.
Also I would not consider him an expert in anything ML, though he probably has enough of the underlying math to get some things.
Kaku is a media sensationalist; that class of person has a terrible track record. Futurists, that is, people like Aasimov, have an ok track record at predicting the future. Interestingly, early futurist predictions about digital tech were pretty good. For "physical" goods? Not so much. A plausible explanation of this discrepancy is that they didn't predict the breakdown in the historial trend of increasing energy usage. See the Henry Adams curve.
I'm saying explicitly that the words that come out of Mr Kaku's mouth are noise, not signal. If he is right about something, it is in the way a broken clock is occasionally right. I agree with most of what he is saying personally, but that's not relevant.
string field theory is a a "field" of physics which is entirely theoretical and has no experiment data to back it up....
hard to imagine how even the top person in that field would be a top physicist given the large number of top physicists who are doing useful stuff like LIGO, CERN, etc.
The thing I bounced off isn't the high-concept art, or the abstract math. It’s the combination of the two without enough bridge between them. You have to infer too much about how the poetic layer, the mathematical notation, and the actual machinery relate.
You can do mind-expansion by induction in a math journal. This is not that venue. And this project is too good to waste by letting people walk away confused.
I’d love a very plain “one clock, end to end” walkthrough: primitives, composition, graph, rendered result.